Analysis of Cyber Security Attacks and Its Solutions for the Smart grid Using Machine Learning and Blockchain Methods

被引:47
|
作者
Mazhar, Tehseen [1 ]
Irfan, Hafiz Muhammad [2 ]
Khan, Sunawar [2 ]
Haq, Inayatul [3 ]
Ullah, Inam [4 ]
Iqbal, Muhammad [5 ]
Hamam, Habib [6 ,7 ,8 ,9 ]
机构
[1] Virtual Univ Pakistan, Dept Comp Sci, Lahore 51000, Pakistan
[2] Islamia Univ Bahawalpur, Dept Comp Sci, Bahawalnagar 62300, Pakistan
[3] Zhengzhou Univ, Sch Informat Engn, Zhengzhou 450001, Peoples R China
[4] Chungbuk Natl Univ, Chungbuk Informat Technol Educ & Res Ctr BK21, Cheongju 28644, South Korea
[5] Gomal Univ, Inst Comp & Informat Technol, Dera Ismail Khan 29220, Pakistan
[6] Univ Moncton, Fac Engn, Moncton, NB E1A3E9, Canada
[7] Spectrum Knowledge Prod & Skills Dev, Sfax 3027, Tunisia
[8] Int Inst Technol & Management, Libreville, Gabon
[9] Univ Johannesburg, Sch Elect Engn, Dept Elect & Elect Engn Sci, ZA-2006 Johannesburg, South Africa
基金
加拿大自然科学与工程研究理事会;
关键词
smart grid; cyber security; cyberattacks; machine learning; deep learning; data mining; MODEL; MICROGRIDS; ENSEMBLE; DEFENSE; PEER;
D O I
10.3390/fi15020083
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Smart grids are rapidly replacing conventional networks on a worldwide scale. A smart grid has drawbacks, just like any other novel technology. A smart grid cyberattack is one of the most challenging things to stop. The biggest problem is caused by millions of sensors constantly sending and receiving data packets over the network. Cyberattacks can compromise the smart grid's dependability, availability, and privacy. Users, the communication network of smart devices and sensors, and network administrators are the three layers of an innovative grid network vulnerable to cyberattacks. In this study, we look at the many risks and flaws that can affect the safety of critical, innovative grid network components. Then, to protect against these dangers, we offer security solutions using different methods. We also provide recommendations for reducing the chance that these three categories of cyberattacks may occur.
引用
收藏
页数:37
相关论文
共 50 条
  • [21] Security risk models against attacks in smart grid using big data and artificial intelligence
    Ghadi, Yazeed Yasin
    Mazhar, Tehseen
    Aurangzeb, Khursheed
    Haq, Inayatul
    Shahzad, Tariq
    Laghari, Asif Ali
    Anwar, Muhammad Shahid
    PEERJ COMPUTER SCIENCE, 2024, 10
  • [22] An Integrated Security System of Protecting Smart Grid against Cyber Attacks
    Wei, Dong
    Lu, Yan
    Jafari, Mohsen
    Skare, Paul
    Rohde, Kenneth
    2010 INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT), 2010,
  • [23] Computational Intelligence Algorithms Analysis for Smart Grid Cyber Security
    Wang, Yong
    Ruan, Da
    Xu, Jianping
    Wen, Mi
    Deng, Liwen
    ADVANCES IN SWARM INTELLIGENCE, PT 2, PROCEEDINGS, 2010, 6146 : 77 - +
  • [24] Detecting false data attacks using machine learning techniques in smart grid: A survey
    Cui, Lei
    Qu, Youyang
    Gao, Longxiang
    Xie, Gang
    Yu, Shui
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2020, 170
  • [25] A review on security analysis of cyber physical systems using Machine learning
    Ahmed Jamal A.
    Mustafa Majid A.-A.
    Konev A.
    Kosachenko T.
    Shelupanov A.
    Materials Today: Proceedings, 2023, 80 : 2302 - 2306
  • [26] A Novel Approach Based on Machine Learning, Blockchain, and Decision Process for Securing Smart Grid
    Chibi, Nabil Tazi
    Oualhaj, Omar Ait
    Fihri, Wassim Fassi
    El Ghazi, Hassan
    IEEE ACCESS, 2024, 12 : 33190 - 33199
  • [27] Anomaly detection in cyber security attacks on networks using MLP deep learning
    Teoh, T. T.
    Chiew, Graeme
    Franco, Edwin J.
    Ng, P. C.
    Benjamin, M. P.
    Goh, Y. J.
    2018 INTERNATIONAL CONFERENCE ON SMART COMPUTING AND ELECTRONIC ENTERPRISE (ICSCEE), 2018,
  • [28] Classification of smart grid stability prediction using cascade machine learning methods and the internet of things in smart grid
    Mithat Önder
    Muhsin Ugur Dogan
    Kemal Polat
    Neural Computing and Applications, 2023, 35 : 17851 - 17869
  • [29] A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
    Buczak, Anna L.
    Guven, Erhan
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2016, 18 (02): : 1153 - 1176
  • [30] Cyber Security of Smart Grids in the Context of Big Data and Machine Learning
    Dogaru, Delia Ioana
    Dumitrache, Ioan
    2019 22ND INTERNATIONAL CONFERENCE ON CONTROL SYSTEMS AND COMPUTER SCIENCE (CSCS), 2019, : 61 - 67